I computed an FFT on the raw depth logs from the recovered DSTs and plotted periodograms.
For most of the sharks, diurnal patterns with periods of 6, 12 and 24h are visible in the periodograms.
I have to still pre-process the data, i.e. smooth them (rolling mean?) and filter out the time after the sharks’ deaths.

Sharks that stayed in the Oosterschelde

Tag 295 logged for 46 days between 2018-07-19 and 2018-09-03.

Tag 319 logged for 32 days between 2018-07-19 and 2018-08-20.

Tag 322 logged for 33 days between 2018-07-19 and 2018-08-21.

Sharks that swam to the OWF

Tag 304 logged for 22 days between 2019-07-11 and 2019-08-02.

Tag 310 logged for 46 days between 2019-07-11 and 2019-08-26.

Tag 312 logged for 40 days between 2019-07-12 and 2019-08-21.

Sharks that logged for >1 year

tag 308
tag 321

Tag 308 logged for 366 days between 2018-08-02 and 2019-08-03.

Tag 321 logged for 485 days between 2018-07-19 and 2019-11-16.

Map

--- title: "Depth logs FFT" description: "FFT periodograms of all 8 recovered tags." # author: "Lotte Pohl" execute: echo: false include: false output: html_document: df_print: paged theme: readable # toc_float: true toc: true # number_sections: false # toc_depth: 2 date: 3.13.2023 editor_options: chunk_output_type: console knitr: opts_chunk: collapse: true format: html: page-layout: article code-tools: true fig-width: 8 fig-height: 5 toc: true image: image.PNG --- ```{r libraries} # WORKSPACE #### library(dplyr) library(lubridate) library(plotly) library(pracma) library(psdr) library(ggplot2) library(ggsci) library(sf) ``` ```{r workspace} # rm(list = ls()) dir_path <- "C:/Users/lotte.pohl/Documents/github_repos/ADST_Mustelus_asterias" # source(paste0(dir_path, "/02_scripts/02_load_data/load_depth_temp_logs.R")) source(paste0(dir_path, "/02_scripts/04_analyses/FFT/calculate_fft_psd.R")) source(paste0(dir_path, "/02_scripts/05_plots_maps/plot_fft_periodogram.R")) source(paste0(dir_path, "/02_scripts/05_plots_maps/plot_dst_pressure_temp.R")) source(paste0(dir_path, "/02_scripts/02_load_data/load_dst_geolocation_output.R")) source(paste0(dir_path, "/02_scripts/05_plots_maps/base_map.R")) # todo: load 2 scripts (fft calc and periodogram plot) and do ggplotly() and maybe superpose them? ``` ```{r depthlogs_summary} summary_depthlogs <- masterias_depth_temp %>% group_by(tag_serial_number) %>% summarise(start_date = lubridate::date(date_time %>% min()), end_date = lubridate::date(date_time %>% max()), log_time_d = difftime(end_date, start_date, units = "days") %>% as.numeric()) ``` * I computed an FFT on the raw depth logs from the recovered DSTs and plotted periodograms. * For most of the sharks, diurnal patterns with periods of 6, 12 and 24h are visible in the periodograms. * I have to still pre-process the data, i.e. smooth them (rolling mean?) and filter out the time after the sharks' deaths. # Sharks that stayed in the Oosterschelde ::: {.column-page-inset} :::{.panel-tabset} ## tag 295 ```{r tag295} #| include: true #| layout-ncol: 2 plot_dst_295 #%>% ggplotly() pgram_295 #%>% ggplotly() ``` Tag 295 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293295") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293295") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293295") %>% dplyr::select(end_date) %>% pull()`. ## tag 319 ```{r tag319} #| include: true #| layout-ncol: 2 plot_dst_319 #%>% ggplotly() pgram_319 #%>% ggplotly() ``` Tag 319 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293319") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293319") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293319") %>% dplyr::select(end_date) %>% pull()`. ## tag 322 ```{r tag322} #| include: true #| layout-ncol: 2 ##| fig-height: 4 #| column: page #| fig-subcap: #| - "" plot_dst_322 #%>% ggplotly() pgram_322 #%>% ggplotly() ``` Tag 322 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293322") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293322") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293322") %>% dplyr::select(end_date) %>% pull()`. ::: ::: # Sharks that swam to the OWF ::: {.column-page-inset} :::{.panel-tabset} ## tag 304 ```{r tag304} #| include: true #| layout-ncol: 2 ##| fig-height: 4 #| column: page #| fig-subcap: #| - "" plot_dst_304 #%>% ggplotly() pgram_304 #%>% ggplotly() ``` Tag 304 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293304") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293304") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293304") %>% dplyr::select(end_date) %>% pull()`.   ## tag 310 ```{r tag310} #| include: true #| layout-ncol: 2 ##| fig-height: 4 #| column: page #| fig-subcap: #| - "" plot_dst_310 #%>% ggplotly() pgram_310 #%>% ggplotly() ``` Tag 310 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293310") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293310") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293310") %>% dplyr::select(end_date) %>% pull()`.   ## tag 312 ```{r tag312} #| include: true #| layout-ncol: 2 ##| fig-height: 4 #| column: page #| fig-subcap: #| - "" plot_dst_312 #%>% ggplotly() pgram_312 #%>% ggplotly() ``` Tag 312 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293312") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293312") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293312") %>% dplyr::select(end_date) %>% pull()`.   ::: ::: # Sharks that logged for >1 year ::: {.column-page-inset} :::{.panel-tabset} ## tag 308 ```{r tag308} #| include: true #| layout-ncol: 2 ##| fig-height: 4 #| column: page #| fig-subcap: #| - "" plot_dst_308 #%>% ggplotly() pgram_308 #%>% ggplotly() ``` Tag 308 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293308") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293308") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293308") %>% dplyr::select(end_date) %>% pull()`.   ## tag 321 ```{r tag321} #| include: true #| layout-ncol: 2 ##| fig-height: 4 #| column: page #| fig-subcap: #| - "" plot_dst_321 #%>% ggplotly() pgram_321 #%>% ggplotly() ``` Tag 321 logged for `r summary_depthlogs %>% filter(tag_serial_number == "1293321") %>% dplyr::select(log_time_d) %>% pull()` days between `r summary_depthlogs %>% filter(tag_serial_number == "1293321") %>% dplyr::select(start_date) %>% pull()` and `r summary_depthlogs %>% filter(tag_serial_number == "1293321") %>% dplyr::select(end_date) %>% pull()`.   ::: ::: # Map ::: {.column-screen} ```{r} #| include: true #| layout-ncol: 1 ##| fig-height: 4 #| column: page #| fig-subcap: #| - "" col_fun <- ggsci::pal_locuszoom()(masterias_depth_temp %>% filter(!tag_serial_number %in% tag_serial_number_omit) %>% unique() %>% length()) pal <- leaflet::colorFactor(col_fun, domain = masterias_depth_temp %>% filter(!tag_serial_number %in% tag_serial_number_omit) %>% dplyr::select(tag_serial_number) %>% unique() %>% pull()) # for the long term DST tracks pal_dst <- colorNumeric(palette = "magma", domain = c(masterias_dst_geolocation_output$date_time %>% min(), masterias_detections_clean$date_time %>% max())) # mpts_all$date_time, masterias_detections_clean$date_time # mpts_short <- mpts_all %>% filter(!tag_serial_number == c("1293308", "1293321")) legend_dates = c("2018-08-01", "2018-11-01", "2019-02-01", "2019-05-01", "2019-08-01", "2019-11-01") base_map %>% hideGroup(c("stations", "released tags", "areas")) %>% # add tag 295 ##### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293295"), lat = ~detection_latitude, lng = ~detection_longitude, color = ~pal(tag_serial_number), weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 295") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293295"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293295"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293295"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal(tag_serial_number), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 295") %>% # add tag 304 ##### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293304"), lat = ~detection_latitude, lng = ~detection_longitude, color = ~pal(tag_serial_number), weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 304") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293304"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293304"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293304"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal(tag_serial_number), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 304") %>% # add tag 310 ##### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293310"), lat = ~detection_latitude, lng = ~detection_longitude, color = ~pal(tag_serial_number), weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 310") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293310"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293310"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293310"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal(tag_serial_number), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 310") %>% # add tag 312 ##### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293312"), lat = ~detection_latitude, lng = ~detection_longitude, color = ~pal(tag_serial_number), weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 312") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293312"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293312"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293312"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal(tag_serial_number), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 312") %>% # add tag 319 ##### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293319"), lat = ~detection_latitude, lng = ~detection_longitude, color = ~pal(tag_serial_number), weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 319") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293319"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293319"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293319"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal(tag_serial_number), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 319") %>% # add tag 322 ##### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293322"), lat = ~detection_latitude, lng = ~detection_longitude, color = ~pal(tag_serial_number), weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 322") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293322"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293322"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = ~pal(tag_serial_number), weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293322"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal(tag_serial_number), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 322") %>% # add tag 308 #### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293308"), lat = ~detection_latitude, lng = ~detection_longitude, color = "#B5B5B5", weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 308 (female)") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293308"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = "#B5B5B5", weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293308"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = "#B5B5B5", weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293308"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal_dst(date_time), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 308 (female)") %>% # add tag 321 #### addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293321"), lat = ~detection_latitude, lng = ~detection_longitude, color = "#B5B5B5", weight = 3, opacity = 0.6, label = ~tag_serial_number, group = "tag 321 (male)") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293321"), lat = ~detection_latitude_mean, lng = ~detection_longitude_mean, color = "#B5B5B5", weight = 1, fillOpacity = 0.2, opacity = 0.2, dashArray = "5,5", label = ~paste0(tag_serial_number, ", mean track"), group = "mean tracks") %>% addPolylines(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293321"), lat = ~detection_latitude_mode, lng = ~detection_longitude_mode, color = "#B5B5B5", weight = 1, fillOpacity = 0.3, dashArray = "1,7", label = ~paste0(tag_serial_number, ", mode track"), group = "mode tracks") %>% addCircleMarkers(data = masterias_dst_geolocation_output %>% filter(tag_serial_number == "1293321"), lat = ~detection_latitude, lng = ~detection_longitude, fillColor = ~pal_dst(date_time), radius = 5, weight = 0, fillOpacity = 0.8, label = ~paste0(format(date_time,"%F"), ", ", sex), group = "tag 321 (male)") %>% # ADD CONTROLS ##### leafem::addMouseCoordinates() %>% addLayersControl(position = "topright", baseGroups = c("EMODnet bathymetry", "satellite"), overlayGroups = c("tag 295", "tag 304", "tag 310", "tag 312", "tag 319", "tag 322", "tag 308 (female)", "tag 321 (male)","mean tracks", "mode tracks", "wrecks, OWFs, cables"), options = layersControlOptions(collapsed = FALSE)) %>% hideGroup(c("tag 308 (female)", "tag 321 (male)", "mean tracks", "mode tracks", "wrecks, OWFs, cables")) %>% addLegend(position = "topleft", colors = legend_dates %>% as.POSIXct() %>% pal_dst(), labels = legend_dates, opacity = 1, title = "Dates") ``` :::